Recurring User Interface Action Detection with Partition Graphs
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Solution Overview
Problem
Existing systems struggle to accurately detect and automate recurring patterns of user interface actions in software applications, leading to inefficiencies in tasks that require repetitive interactions.
Innovation Solution
A method involving the analysis of recorded sequences of user interface actions to identify split points, generate a linear partition graph, and utilize paths within this graph to detect recurring patterns, enabling automation of these actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing systems attempt to detect recurring patterns of user interface actions, then automation capability is improved, but detection accuracy deteriorates
Solution Approach 1:
The patent segments the sequence of user interface commands by identifying split points that divide the sequence into meaningful segments. These segments are then used to construct paths in a linear partition graph, allowing the system to detect recurring patterns by analyzing relationships between segments rather than treating the entire command sequence as a single unit. This segmentation enables more accurate pattern recognition while maintaining automation capability.
2Productivity
If the system analyzes sequences of user interface commands to identify patterns, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent transforms the one-dimensional sequence of commands into a two-dimensional linear partition graph structure by introducing split points as vertices and defining paths between them. This dimensional transformation allows the system to represent command sequences as navigable paths through a graph, simplifying the pattern detection process while improving productivity by enabling efficient recognition of recurring action patterns.
3Measurement precision
If the system uses linear partition graphs to detect patterns, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The linear partition graph is constructed by segmenting the command sequence at identified split points, creating a simplified representation where paths between vertices correspond to meaningful command sequences. This segmentation reduces the complexity of processing the entire command sequence by breaking it down into manageable segments that can be systematically analyzed through graph traversal algorithms.
Solution Approach 2:
The linear partition graph acts as an intermediary structure between the raw command sequence and the pattern detection process. By representing commands as paths through the graph, the system simplifies pattern recognition while maintaining high measurement precision, as the graph structure captures the essential relationships between commands without requiring complex direct analysis of the entire sequence.
Data Source
AI summary
An example method of detecting recurring patterns of user interface actions comprises: receiving a sequence of user interface commands; identifying a plurality of split points of the sequence of user interface commands; generating a linear partition graph comprising a plurality of vertices corresponding to a subset of split points; identifying a subset of paths in the linear partition graph; and utilizing the subset of paths for identifying a recurring pattern in a new sequence of user interface commands.